Examining the effectiveness of health food advertising based on Optimal Arousal Theory

Abstract

With the increasing awareness of health and the widespread adoption of social media advertising, health food advertising has become an important source of information influencing consumer decision-making. However, existing studies have primarily focused on the effects of attitudes or behaviors, with limited attention to the underlying psychological mechanisms. Therefore, this study applies optimal arousal theory to examine how expertise and trustworthiness in health food advertising influence consumers’ purchase intention through perceived information relevance. The findings indicate that both expertise and trustworthiness positively affect perceived information relevance, which in turn significantly enhances purchase intention. These results suggest that individuals tend to pursue an optimal level of stimulation, and when advertising information evokes an appropriate level of psychological arousal and aligns with personal needs, it is more likely to facilitate positive behavioral responses. In addition to confirming the importance of perceived information relevance, this study extends optimal arousal theory from the level of sensory stimulation to the cognitive level, thereby advancing the development of optimal arousal theory research.

Keywords: {'name': 'Optimal Arousal Theory, Expertise, Trustworthiness, Perceived Information Relevance'}

Authors & affiliations

Chih-Yu Wang
I-Shou University

Ren-Fang Chao
Department of Leisure Management, I-Shou University

Chor-Sum Au-Yeung
I-Shou University

Yu-Lung Wu
I-Shou University

Deposited references

Supplied references, not a list of publications citing this article.

DOI: 10.4018/JOEUC.2020010101

DOI: 10.1108/RIBS-07-2020-0089

DOI: 10.1016/j.joitmc.2025.100580

DOI: 10.1037/0033-2909.103.3.411

DOI: 10.1177/23197145241313317

DOI: 10.1007/s44202-025-00333-8

DOI: 10.1111/ijcs.12917

DOI: 10.1016/j.actpsy.2024.104177

Belch, G. E., & Belch, M. A. (2004). Advertising and Promotion: An Integrated Marketing Communications Perspective (6 th Ed.). New York, NY: McGraw-Hill.

DOI: 10.1016/j.jretconser.2023.103336

DOI: 10.1002/mar.21977

DOI: 10.1080/0361073X.2022.2051967

DOI: 10.1177/0047287513481274

DOI: 10.1080/00913367.2022.2154721

DOI: 10.29303/jmm.v9i2.538

DOI: 10.1016/j.jhtm.2022.05.005

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2017). Multivariate Data Analysis, PEL, ED (7th Ed.). Essex, UK: Bookman.

DOI: 10.1080/03637750903310360

DOI: 10.1007/s11002-022-09657-0

DOI: 10.1007/s11747-014-0403-8

DOI: 10.1108/QMR-12-2017-0175

DOI: 10.1016/j.jretconser.2019.01.005

DOI: 10.1016/j.ijinfomgt.2019.07.009

DOI: 10.1016/j.jbusres.2021.05.024

Kline, R. B. (2023). Principles and Practice of Structural Equation Modeling (5th Ed.). New York, NY: Guilford publications.

DOI: 10.1080/15332667.2023.2216373

DOI: 10.1080/10496491.2022.2060410

DOI: 10.1080/02650487.2021.2020563

DOI: 10.2501/JAR-2024-019

DOI: 10.3389/fpsyg.2022.940649

DOI: 10.1016/j.jbusres.2024.114874

DOI: 10.1016/j.jcps.2014.11.006

DOI: 10.4018/IJESMA.296575

DOI: 10.1146/annurev-orgpsych-110721-040030

DOI: 10.1007/s00221-017-4922-7

DOI: 10.1080/08911762.2021.1980932

DOI: 10.1080/10941665.2025.2470658

DOI: 10.1080/15323269.2023.2223117

DOI: 10.1016/j.jbusres.2022.04.026

DOI: 10.1080/23311975.2021.2000697

DOI: 10.1016/j.tourman.2025.105208

DOI: 10.2501/JAR-2017-042

DOI: 10.1006/obhd.1994.1011

DOI: 10.3389/fpsyg.2024.1379992

DOI: 10.1108/K-04-2023-0627

DOI: 10.1002/mar.20862

DOI: 10.1108/IMDS-07-2022-0430